Fusion: Practice and Applications

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https://doi.org/10.54216/FPA

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Volume 21 , Issue 2 , PP: 199-210, 2026 | Cite this article as | XML | Html | PDF | Full Length Article

Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots

Mohammed Rabeea Hashim Al-Dahhan 1 * , Mahmood Abdulrazzaq Alsaadi 2 , Ruqayah R. Al-Dahhan 3 , Salah A. Aliesawi 4 , Omar Q. Mohsin 5

  • 1 College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq - (mohammed.rabeea@uoanbar.edu.iq)
  • 2 Computer Science Department, University of Al-Maarif, Ramadi, Anbar, Iraq - (alsaadi.m@uoa.edu.iq)
  • 3 College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq - (ruqayah85@uoanbar.edu.iq)
  • 4 College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq - (salah_eng1996@uoanbar.edu.iq)
  • 5 Senior SoC Debug Engineer/Tech lead; intel corporation, USA - (omar.mohsin@intel.com)
  • Doi: https://doi.org/10.54216/FPA.210213

    Received: April 18, 2025 Revised: June 30, 2025 Accepted: August 29, 2025
    Abstract

    To facilitate the practical deployment of robotics, efficient path planning is essential to ensure that robotic movement is accurate, safe, and goal-oriented. This study explores new approaches to map adaptation and path optimization for robot navigation between specified locations. The initial phase of the research involves designing an environment that enables the safe operation of robots. Subsequently, the collected data is processed to construct a graph using Dijkstra’s algorithm, which is employed to determine the shortest path between key points. When multiple paths are available, the algorithm selects the most efficient one, while ensuring safety in point-to-point transitions and when navigating around obstacles. In addition to this, a reinforced method is introduced to enhance the security of path planning. This approach expands the original trajectory to incorporate a safety buffer equal to half of the robot’s safety radius, thus maintaining a safe distance along the traveled route. The key contribution of this work lies in the development of novel maps featuring secure pathways, which can be utilized by optimization algorithms to improve navigation in unfamiliar terrains. Experimental results using PRM* and RRT* validate the accuracy of these maps, especially in complex, maze-like environments.

    Keywords :

    Mobile robot , Path planning , Reshaping , Navigation , Map Reconstruction , Safety

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    Cite This Article As :
    Rabeea, Mohammed. , Abdulrazzaq, Mahmood. , R., Ruqayah. , A., Salah. , Q., Omar. Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots. Fusion: Practice and Applications, vol. , no. , 2026, pp. 199-210. DOI: https://doi.org/10.54216/FPA.210213
    Rabeea, M. Abdulrazzaq, M. R., R. A., S. Q., O. (2026). Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots. Fusion: Practice and Applications, (), 199-210. DOI: https://doi.org/10.54216/FPA.210213
    Rabeea, Mohammed. Abdulrazzaq, Mahmood. R., Ruqayah. A., Salah. Q., Omar. Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots. Fusion: Practice and Applications , no. (2026): 199-210. DOI: https://doi.org/10.54216/FPA.210213
    Rabeea, M. , Abdulrazzaq, M. , R., R. , A., S. , Q., O. (2026) . Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots. Fusion: Practice and Applications , () , 199-210 . DOI: https://doi.org/10.54216/FPA.210213
    Rabeea M. , Abdulrazzaq M. , R. R. , A. S. , Q. O. [2026]. Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots. Fusion: Practice and Applications. (): 199-210. DOI: https://doi.org/10.54216/FPA.210213
    Rabeea, M. Abdulrazzaq, M. R., R. A., S. Q., O. "Optimizing Navigation: Adaptive Map Reshaping and Shortest Path Analysis for Mobile Robots," Fusion: Practice and Applications, vol. , no. , pp. 199-210, 2026. DOI: https://doi.org/10.54216/FPA.210213